Instructions to use connectivity/bert_ft_qqp-35 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/bert_ft_qqp-35 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/bert_ft_qqp-35")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/bert_ft_qqp-35") model = AutoModelForSequenceClassification.from_pretrained("connectivity/bert_ft_qqp-35", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/bert_ft_qqp-35: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/bert_ft_qqp-35/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/bert_ft_qqp-35/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/bert_ft_qqp-35/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- f48119ae379917f545e4a15326317875d5de018777e0d15350dc0999e2031f90
- Size of remote file:
- 438 MB
- SHA256:
- d0d94826f472ecfae9ad77c3184fa93870bb732cfa77ea978e1e4921ff0527f8
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